Remote sensing of precipitable water vapour and cloud cover for site selection of the European Extremely Large Telescope (E-ELT) using MERIS

Size: px
Start display at page:

Download "Remote sensing of precipitable water vapour and cloud cover for site selection of the European Extremely Large Telescope (E-ELT) using MERIS"

Transcription

1 Remote sensing of precipitable water vapour and cloud cover for site selection of the European Extremely Large Telescope (E-ELT) using MERIS H. Kurlandczyk 1 M.Sarazin 1 1 European Organisation for Astronomical Research in the Southern Hemisphere (ESO), Karl-Schwarzschild-Strasse 2, D Garching bei Muenchen, Germany ABSTRACT Remotely sensed data can be of great interest for the site selection of astronomical observatories. In particular, candidate sites of the future European Extremely Large Telescope (E-ELT) of 3-6 m diameter from ESO need to be assessed and analytically compared in their observing characteristics. Parameters such as cloud cover and precipitable water vapor which are important for optical and infrared astronomical observations have been assessed with the MEdium Resolution Imaging Spectrometer (MERIS) instrument on the Envisat satellite with a resolution of 1km pixel. A validation of the data was made by comparing MERIS data and in situ measurement available from ESO observatories in Chile, La Silla and Paranal, combined with lower resolution values from the GOES weather satellite. A detailed analysis of daytime cloud cover from 22 to 26 at four sites under study both in the northern and in the southern hemisphere for the E- ELT is presented. Keywords: Cloud cover, Water vapour, Site survey, telescope, MERIS 1. INTRODUCTION The European Extremely Large Telescope (E-ELT) is a project for the next-generation optical telescopes by the European Southern Observatory with a mirror diameter of 42 meters. Current fabrication technology limits single mirrors to being roughly 8 meters in a single piece. The next-largest telescopes currently in use are the Gran Telescopio Canarias and Southern African Large Telescope, which each use hexagonal mirrors fitted together to make a mirror more than 1 meters across. The E-ELT would need to use a similar design. In addition, E-ELT would also need to use techniques to work around atmospheric distortion of incoming light, known as adaptive optics. Project E-ELT has the aim of observing the Universe in greater detail than even the Hubble Space Telescope. A mirror of approximately 42 meters would allow the study of the atmospheres of extrasolar planets. The 5-mirror anastigmat design is estimated to cost 8 million and could be completed by 217. The location of the biggest telescope ever built has yet to be defined and plays a crucial role for the performance of the instrument. ESO conducts a systematic approach on site comparison and among others; we investigate the usefulness of medium resolution polar satellites to estimate parameters such as cloud cover and precipitable water vapour at selected candidate sites. In order to avoid atmospheric turbulences, observatories are often located on high sites in mountainous regions. A resolution of about 1km is therefore an interesting asset in these regions where climatological conditions change rapidly with the local orography. The MEdium Resolution Imaging Spectrometer (MERIS) instrument on the Envisat satellite from ESA was considered as a potential source of data for this purpose. First, a verification between MERIS data and the data used by ESO in the past years was made. This ESO data stems from a combination of in-situ measurements and GOES satellite images with a lower resolution than MERIS. The period of the comparison is from 22 to 26 which corresponds to the availability of MERIS data and the location where the verification took place are the two observatories La Silla and Paranal where ESO collects data every 3 hours for years now. Second, an analysis on an application on site testing was conducted where the 14.3 UTC MERIS data was compared to GOES night data, this lead to an evaluation of the error done between night and day measurement for both cloud cover and PWV. Third the

2 impact of window size was analyzed on a coarse terrain and finally four candidate sites - Aklim in Morocco, Roque de los muchachos on the Canary Islands in Spain, Macon in the Argentinean Andes and Paranal in Chile where ESO s very large telescope is already operational - were compared with the MERIS data set at a resolution of 1km. Fig m Diameter E-ELT design ( 2.1 MERIS data 2. VERIFICATION OF MERIS DATA MERIS is a passive imaging spectrometer that looks in the nadir direction. It performs simultaneously spatial and spectral imaging of the Earth, it is one of the main instruments on-board the European Space Agency (ESA)'s Envisat platform.the spatial resolution of the detectors provides for samples every 3 m this is known as the 'Full Resolution (FR)' product. In this study the Reduced Resolution was used 1,2 km by 1,2 km. The total field of view of MERIS is 68.5 degrees around nadir (yielding a swath width of 115 km), which is enough to collect data for the entire earth every 3 days (in equatorial regions). Polar regions are visited more frequently due to the convergence of orbits. The observation is performed simultaneously in 15 programmable spectral bands, ranging from the visible to the near infrared (39 nm to 14 nm). Each of these 15 bands is programmable in position and in width. The water vapor retrieval algorithms for MERIS are based on the work of Bartsch, (1996) and Bartsch et al. (1997). The general algorithm approach is to relate the PWV content to the ratio of MERIS channels 14 and 15, located at 89 nm and 9 nm, respectively (Fisher, 1997). The cloud albedo and cloud optical thickness are estimated from measurements of the MERIS channel centered at nm. An algorithm is established to transform the radiance measurements into hemispherical quantities by integration over viewing angles, since clouds do not reflect the sunlight isotropically. 2.2 GOES data In order to make a verification of the MERIS data, measurements of cloud cover and PWV are derived from a combination of satellite observations made by passive remote sensing at ±1.7μm and ±6.5μm from the satellite GOES

3 and in situ measurements of temperature and humidity at the observatories La Silla and Paranal. Satellite observations at about 6.5μm are sensitive to emissions from WV resident in the layer between about 6mb (±44m) and 3mb (±9m). If high altitude (cirrus) clouds exist above this layer their presence and thickness can be determined. The other channel is used to detect clouds at middle level. Low levels clouds, with a cloud top temperature comparable to the ground conditions, are difficult to detect with this method. The analysis can be performed for a specific site or an area of interest. Above a particular location, a more realistic picture of the observable sky is obtained using a 9 (3 3)-pixel area of 12x12 km. For the area analysis the 9-pixel template is passed over the area of interest, counts compiled and contours drawn. For a detailed description of the methodology employed in the above mentioned studies please consult Erasmus & Sarazin (2), Erasmus & Sarazin (22). 2.3 Time resolution In order to be able to use MERIS data, a verification process was established where the results of the GOES analysis described previously were compared to the MERIS output. The MERIS overfly time of the region in Chile were both observatories La Silla and Paranal are located is varying between 13.5 and 14.5 UTC every two or three days. The GOES measurement have a much higher time resolution of every 3 hours. The MERIS data was compared to the GOES measurement of the corresponding day at 15. UTC. Unfortunately for optical and IR astronomy this measurement time is only during the day and therefore one has to be careful with the interpretation of MERIS data for site selection since it does not contain any data during the night. 2.4 Cloud cover The cloud cover GOES measurements are done on a window size of 12km square while MERIS resolution is 1 km. Therefore MERIS data were combined out of a 12 x 12 pixel square and compared with the GOES data in order to have an identical window size. The 12 km window on top of the observatories corresponds to a viewing angle of 67 degrees for clouds at 3km above ground. Fractional cloud cover over la Silla and Paranal observatories obtained with the two methods between April 22 and August 26 were compared. The following tables show the percentage of the measurement where both methods agree or not. The results are classified in three categories hit, neutral and miss defined as follows, Hit: x< 25% Neutral; Miss: 25%<x<5% 5%<x Where x is the difference between both measurements. Table 1 Percentage of the agreement of GOES data and MERIS data for cloud cover analysis. Window size 12km x 12km. Hit, neutral and miss are defined as Hit: x< 25%, Neutral; 25%<x<5% Miss: 5%<x where x is the difference between both measurements. Paranal clear fraction: MERIS 93%, GOES 96% La Silla clear fraction: MERIS 85%, GOES 8% Hit % Hit 43 93% Neutral 5 1% Neutral 16 3% Miss 5 1% Miss 17 4% Sum 463 1% Sum 463 1% Table 1 shows that for cloud cover measurements both methods have similar results within +/-5%. The scatter increases with cloudiness. 2.5 Precipitable water vapor For the water vapor, instead of using 12 km window size as for the cloud cover, a more sensible comparison of both data sets is to use a window size of 2 km which corresponds to the area just above the observatory. If we would use an equivalent 12 km window size with MERIS we would end up with water vapour values of regions below the

4 GOES PWV (mm) Paranal PWV (mm) observatory. The GOES measurements combined with the pressure and temperature are described in detail in Erasmus & Sarazin (22) PWV Envisat PWV GOES Overfly Aug-2 Oct-2 Jan-3 Apr-3 Jun-3 Aug-3 Nov-3 Aug-4 Oct-4 Nov-4 Jan-5 Mar-5 May-5 Jun-5 Sep-5 Nov-5 Jan-6 Apr-6 Jun-6 Aug-6 Fig. 2. Comparison of GOES and MERIS measurements of PWV on Paranal between 22 and 26. MERIS Window size is 2km x 2km. The GOES and MERIS measurements are qualitatively very similar. However MERIS is often measuring slightly higher values during humid events. For color graph, please refer to electronic format. Paranal PWV (mm) 1% 5% 9% GOES 15 h MERIS Paranal Correlation Factor PWV =, y =.5196x MERIS PWV (mm) Fig. 3. Correlation between GOES and MERIS measurements of PWV on Paranal between 22 and 26. MERIS Window size is 2km x 2km.

5 GOES PWV (mm) La Silla PWV (mm) PWV Envisat PWV GOES Overfly Aug-2 Dec-2 Mar-3 Jun-3 Aug-3 Oct-3 Jun-4 Sep-4 Oct-4 Dec-4 Jan-5 Mar-5 May-5 Jul-5 Sep-5 Nov-5 Jan-6 Apr-6 Jun-6 Aug-6 Fig. 4. Comparison of GOES and MERIS measurements of PWV on La Silla between 22 and 26. MERIS Window size is 2km x 2km. The GOES measurements seem to fit pretty well the MERIS measurement. As opposed to the Paranal situation GOES measurement are higher than the MERIS ones. For color graph, please refer to electronic format. La Silla PWV (mm) 1% 5% 9% GOES 15h MERIS LA SILLA Correlation factor =, y =.5938x MERIS PWV (mm) Fig. 5. Correlation between GOES and MERIS measurements of PWV on LA SILLA between 22 and 26. MERIS Window size is 2km x 2km. A significative offset of 1.5 mm can be noticed for the GOES measurement especially in the lower PWV values. 3. APPLICATION ON SITE TESTING 3.1 Usefulness of MERIS daytime measurement for the assessment of nighttime quality What counts for an optical telescope is the amount of clear night where scientists are able to observe, the verification of the MERIS data has been done with data taken from both satellites at the same time. Now in order to estimate the

6 misinterpretation we could do by using MERIS we compare the 3-hourly GOES night data with the MERIS day data taken around 14 UT. First, a cloud cover analysis is being done with a window size of 12 km x 12 km and second, PWV is statistically analysed with a window size of 2 km. Table 2. Comparison between GOES and MERIS amounts of clear nights that would be interpreted with both satellites. Clear nights are defined as 1% free of cloud. MERIS Window size is 12km x 12km. GOES measurements are taken during the night as opposed to MERIS that always measures around 14 UTC. Time period is between 22 and 26. Number of clear nights Paranal La Silla GOES Fraction of clear nights 93% 75% GOES Fraction of clear sky measurements at 15 UT 93% 8% MERIS Fraction of clear sky around 14 UC 96% 85% On both Chilean sites MERIS satellite is more optimistic than GOES, with up to 1% error at La Silla. The difference between night or day seem to be different from site to site. Interpretation of clear night should be taken with care using MERIS data. Paranal PWV (mm) 1% 5% 9% La Silla PWV (mm) 1% 5% 9% GOES night GOES night GOES 15 h GOES 15h MERIS MERIS PWV GOES night normal.8 PWV GOES night normal.6 PWV GOES night cumulative normal PWV GOES 15h normal.6 PWV GOES night cumulative normal PWV GOES 15h normal.4 PWV GOES 15h cumulative normal PWV MERIS normal.4 PWV GOES 15h cumulative normal MERIS normal PWV MERIS cumulative normal MERIS cumulative normal Paranal PWV (mm) La Silla PWV (mm) Fig. 6. Comparison of the normal of both GOES during day, during the night and MERIS measurements of PWV in Paranal and La Silla. Window size is 2km x 2km. For the water vapour the difference between night and day of the two GOES measurements is below.8. Time period is between 22 and 26. For color graph, please refer to electronic format.

7 3.2 Influence of window size over sites with variable orography The main reason to use MERIS instead of GOES is the possibility to analyze cloud cover and PWV with a better resolution. Since observatories are often located on high sites, the coarse mountainous terrain presents rapidly changing climate around the sites. It is therefore of great interest to analyze how cloud cover and PWV values are altered by changing the window size. For this analysis we chose the site Roque de Los Muchachos on La Palma, Canary island (Spain) which presents these coarse geographical features. Figure 8 shows the Output of the Earth Observation Grid Processing-on-Demand from ESA/ESRIN tool to extract MERIS data. The white pixel shows clouds and the green ones correspond to clear sky. This image is characteristic of the island where the clouds are often located under the summit where the observation site would be located. In this case the measurement would be classified as clear night for a small window size such as 1 km and as non-clear night if the window size is 12 km.table 5 indicates the huge difference in fraction of clear days by changing the window size. Although there is another effect that has to be taken into account, by increasing the window size we also increase the probability to have a cloud in the field of view. Fig. 7. Output of the Earth Observation Grid Processing-on-Demand from ESA/ESRIN tool to extract MERIS data. The figure shows La Palma Island with Roque de los Muchachos on top of the Volcano. The white pixels correspond to clouds and the green ones to clear sky. This situation is common on La Palma because the temperature inversion resides below the summit. Window Size is 12 x 12 km and the Pixel size is 1 km. For color graph, please refer to electronic format. Time period is between 22 and 26. Table 3. Comparison of the fraction of clear days that would be interpreted with a window size respectively of 1 km and 12 km with MERIS data. The difference is substantial. Window Size Influence Window size 1km 12km Fraction of clear days 65% 27%

8 Fraction of obeservable nights 4. COMPARATIVE SITE ANALYSIS Figure 8 shows the location of four of the candidate sites for the E-ELT. In this paragraph we compare cloud cover and PWV at all four sites with the MERIS data set. Fig. 8. Location of four candidate sites for the E-ELT. 1% 9% 8% 76% 88% 8% 93% 96% 98% Window Size 12km Window Size 1km 7% 65% 6% 5% 4% 3% 27% 2% 1% % Aklim Macon Paranal Roque de los muchachos Fig. 9. Comparison of clear nights for four E-ELT candidate sites. The interpreted fraction of clear nights has to be taken carefully since MERIS measurements just occur during day time and not at night. Especially Roque de los Muchachos presents a big difference in cloud cover between night and day. MERIS window size is 12 x 12 km and 1x 1 km. Time period is between 22 and 26. For color graph, please refer to electronic format.

9 Aklim PWV (mm) Macon PWV (mm) PWV (mm) window size 1km Paranal PWV (mm) Roque de los muchachos PWV (mm) Cum. Norm. dist Aklim.3 Cum. Norm. dist Macon.2 Cum. Norm. dist Paranal Cum. Norm. dist RDM PWV (mm) window size 1km Fig. 1. Comparison of the PWV at four E-ELT candidate sites. The graphs show the normal and the cumulative normal of all four sites. The MERIS Measurements are done with a window size of 1km. Time period is between 22 and 26. For color graph, please refer to electronic format. 5. CONCLUSION Analysis of PWV and cloud cover has shown that MERIS is a powerful tool that can be useful for the site selection process of the E-ELT. The MERIS resolution of 1 km is necessary for some sites where the coarse terrain leads to large changes in climate over small distances. Nevertheless the lack of night data leads to some serious disadvantages for cloud cover estimations over the geostationary satellites such as GOES which has a time resolution of every three hour including night time. All cloud cover results have to be taken carefully since the night climate conditions could be totally different or not. MERIS seems to work well for PWV values which do not present a high difference during the night or during the day. An accurate and systematic analysis of the candidate site should comprise different methods including in situ measurements, geostationary satellites and polar satellites for the better resolution. Acknowledgments: This paper was compiled from research supported by ESA/ESRIN. Miguel Angel Rubio and Olivier Colin are acknowledged for their support in the use of the MERIS data retrieval system: Earth Observation Grid Processing-on-Demand. REFERENCES Bartsch, B. and J. Fischer, 1997: Passive remote sensing of columnar water vapour content over land surfaces. MPIreport No.234, Hamburg, March ISBN Bartsch, B., 1996: Fernerkundung des Wasserdampfgehaltes der Atmosphäre über Land ausrückgestreuter Sonnenstrahlung. Berichte aus dem Zentrum für Meeres- und Klimaforschung, No. 21, 11 pages, Hamburg, Germany. Fischer, J. and R. Bennartz 1997: Retrieval of total water vapour content from MERIS measurements. ESA reference number: PO-TN-MEL-GS-5, published by ESA-ESTEC, Noordwijk, The Netherlands.

10 Erasmus, D.A. & Sarazin, M. 2, Forecasting Precipitable Water Vapor and Cirrus Cloud Cover For Astronomical Observatories: Satellite image processing guided by synoptic model dissemination data. SPIE Conference on Image and Signal Processing for Remote Sensing. IV. Paper SPIE-4168, Barcelona September, 2. Erasmus, D.A. & Sarazin, M. 22, in: J. Vernin, Z. Benkhaldoun, C. Munoz (eds.), Astronomical Site Evaluation in the Visible and Radio Range, (San Franciso: ASP) 266, 31

Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D

Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D Studying cloud properties from space using sounder data: A preparatory study for INSAT-3D Munn V. Shukla and P. K. Thapliyal Atmospheric Sciences Division Atmospheric and Oceanic Sciences Group Space Applications

More information

Statistical Vertical Turbulence Profiles at the Canary Islands Astronomical Sites

Statistical Vertical Turbulence Profiles at the Canary Islands Astronomical Sites Statistical Vertical Turbulence Profiles at the Canary Islands Astronomical Sites B. García-Lorenzo 1, J.J. Fuensalida 1, J. Castro-Almazán 1, & M.A.C. Rodríguez-Hernández 1 (1) Instituto de Astrofísica

More information

16 th IOCCG Committee annual meeting. Plymouth, UK 15 17 February 2011. mission: Present status and near future

16 th IOCCG Committee annual meeting. Plymouth, UK 15 17 February 2011. mission: Present status and near future 16 th IOCCG Committee annual meeting Plymouth, UK 15 17 February 2011 The Meteor 3M Mt satellite mission: Present status and near future plans MISSION AIMS Satellites of the series METEOR M M are purposed

More information

Hyperspectral Satellite Imaging Planning a Mission

Hyperspectral Satellite Imaging Planning a Mission Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute of Aerospace, Langley, VA Outline Objective

More information

How To Calibrate A Mass-Dimm With A Dimm Sensor

How To Calibrate A Mass-Dimm With A Dimm Sensor European Community s Framework Programme 6 EUROPEAN EXTREMELY LARGE TELESCOPE DESIGN STUDY Doc Nº. Issue 1.2 DRAFT 24 th March 2008 Prepared by Approved by Released by Héctor Vázquez Ramió, Antonia M.

More information

Chapter 6 Telescopes: Portals of Discovery. How does your eye form an image? Refraction. Example: Refraction at Sunset.

Chapter 6 Telescopes: Portals of Discovery. How does your eye form an image? Refraction. Example: Refraction at Sunset. Chapter 6 Telescopes: Portals of Discovery 6.1 Eyes and Cameras: Everyday Light Sensors Our goals for learning:! How does your eye form an image?! How do we record images? How does your eye form an image?

More information

Cloud detection and clearing for the MOPITT instrument

Cloud detection and clearing for the MOPITT instrument Cloud detection and clearing for the MOPITT instrument Juying Warner, John Gille, David P. Edwards and Paul Bailey National Center for Atmospheric Research, Boulder, Colorado ABSTRACT The Measurement Of

More information

Multiangle cloud remote sensing from

Multiangle cloud remote sensing from Multiangle cloud remote sensing from POLDER3/PARASOL Cloud phase, optical thickness and albedo F. Parol, J. Riedi, S. Zeng, C. Vanbauce, N. Ferlay, F. Thieuleux, L.C. Labonnote and C. Cornet Laboratoire

More information

Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon

Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon Supporting Online Material for Koren et al. Measurement of the effect of biomass burning aerosol on inhibition of cloud formation over the Amazon 1. MODIS new cloud detection algorithm The operational

More information

Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis

Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis Generated using V3.0 of the official AMS LATEX template Evaluations of the CALIPSO Cloud Optical Depth Algorithm Through Comparisons with a GOES Derived Cloud Analysis Katie Carbonari, Heather Kiley, and

More information

Cloud Masking and Cloud Products

Cloud Masking and Cloud Products Cloud Masking and Cloud Products MODIS Operational Algorithm MOD35 Paul Menzel, Steve Ackerman, Richard Frey, Kathy Strabala, Chris Moeller, Liam Gumley, Bryan Baum MODIS Cloud Masking Often done with

More information

Authors: Thierry Phulpin, CNES Lydie Lavanant, Meteo France Claude Camy-Peyret, LPMAA/CNRS. Date: 15 June 2005

Authors: Thierry Phulpin, CNES Lydie Lavanant, Meteo France Claude Camy-Peyret, LPMAA/CNRS. Date: 15 June 2005 Comments on the number of cloud free observations per day and location- LEO constellation vs. GEO - Annex in the final Technical Note on geostationary mission concepts Authors: Thierry Phulpin, CNES Lydie

More information

Clear Sky Radiance (CSR) Product from MTSAT-1R. UESAWA Daisaku* Abstract

Clear Sky Radiance (CSR) Product from MTSAT-1R. UESAWA Daisaku* Abstract Clear Sky Radiance (CSR) Product from MTSAT-1R UESAWA Daisaku* Abstract The Meteorological Satellite Center (MSC) has developed a Clear Sky Radiance (CSR) product from MTSAT-1R and has been disseminating

More information

REMOTE SENSING OF CLOUD-AEROSOL RADIATIVE EFFECTS FROM SATELLITE DATA: A CASE STUDY OVER THE SOUTH OF PORTUGAL

REMOTE SENSING OF CLOUD-AEROSOL RADIATIVE EFFECTS FROM SATELLITE DATA: A CASE STUDY OVER THE SOUTH OF PORTUGAL REMOTE SENSING OF CLOUD-AEROSOL RADIATIVE EFFECTS FROM SATELLITE DATA: A CASE STUDY OVER THE SOUTH OF PORTUGAL D. Santos (1), M. J. Costa (1,2), D. Bortoli (1,3) and A. M. Silva (1,2) (1) Évora Geophysics

More information

Passive Remote Sensing of Clouds from Airborne Platforms

Passive Remote Sensing of Clouds from Airborne Platforms Passive Remote Sensing of Clouds from Airborne Platforms Why airborne measurements? My instrument: the Solar Spectral Flux Radiometer (SSFR) Some spectrometry/radiometry basics How can we infer cloud properties

More information

150 Watts. Solar Panel. one square meter. Watts

150 Watts. Solar Panel. one square meter. Watts Tool USE WITH Energy Fundamentals Activity land art generator initiative powered by art! 150 Watts 1,000 Watts Solar Panel one square meter 600 Watts SECTION 1 ENERGY EFFICIENCY 250 Watts 1,000 Watts hits

More information

163 ANALYSIS OF THE URBAN HEAT ISLAND EFFECT COMPARISON OF GROUND-BASED AND REMOTELY SENSED TEMPERATURE OBSERVATIONS

163 ANALYSIS OF THE URBAN HEAT ISLAND EFFECT COMPARISON OF GROUND-BASED AND REMOTELY SENSED TEMPERATURE OBSERVATIONS ANALYSIS OF THE URBAN HEAT ISLAND EFFECT COMPARISON OF GROUND-BASED AND REMOTELY SENSED TEMPERATURE OBSERVATIONS Rita Pongrácz *, Judit Bartholy, Enikő Lelovics, Zsuzsanna Dezső Eötvös Loránd University,

More information

Overview of the IR channels and their applications

Overview of the IR channels and their applications Ján Kaňák Slovak Hydrometeorological Institute Jan.kanak@shmu.sk Overview of the IR channels and their applications EUMeTrain, 14 June 2011 Ján Kaňák, SHMÚ 1 Basics in satellite Infrared image interpretation

More information

CLOUD CLASSIFICATION EXTRACTED FROM AVHRR AND GOES IMAGERY. M.Derrien, H.Le Gléau

CLOUD CLASSIFICATION EXTRACTED FROM AVHRR AND GOES IMAGERY. M.Derrien, H.Le Gléau CLOUD CLASSIFICATION EXTRACTED FROM AVHRR AND GOES IMAGERY M.Derrien, H.Le Gléau Météo-France / SCEM / Centre de Météorologie Spatiale BP 147 22302 Lannion. France ABSTRACT We developed an automated pixel-scale

More information

AT&T Global Network Client for Windows Product Support Matrix January 29, 2015

AT&T Global Network Client for Windows Product Support Matrix January 29, 2015 AT&T Global Network Client for Windows Product Support Matrix January 29, 2015 Product Support Matrix Following is the Product Support Matrix for the AT&T Global Network Client. See the AT&T Global Network

More information

Remote Sensing of Clouds from Polarization

Remote Sensing of Clouds from Polarization Remote Sensing of Clouds from Polarization What polarization can tell us about clouds... and what not? J. Riedi Laboratoire d'optique Atmosphérique University of Science and Technology Lille / CNRS FRANCE

More information

A remote sensing instrument collects information about an object or phenomenon within the

A remote sensing instrument collects information about an object or phenomenon within the Satellite Remote Sensing GE 4150- Natural Hazards Some slides taken from Ann Maclean: Introduction to Digital Image Processing Remote Sensing the art, science, and technology of obtaining reliable information

More information

ATM S 111, Global Warming: Understanding the Forecast

ATM S 111, Global Warming: Understanding the Forecast ATM S 111, Global Warming: Understanding the Forecast DARGAN M. W. FRIERSON DEPARTMENT OF ATMOSPHERIC SCIENCES DAY 1: OCTOBER 1, 2015 Outline How exactly the Sun heats the Earth How strong? Important concept

More information

RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR

RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR RESULTS FROM A SIMPLE INFRARED CLOUD DETECTOR A. Maghrabi 1 and R. Clay 2 1 Institute of Astronomical and Geophysical Research, King Abdulaziz City For Science and Technology, P.O. Box 6086 Riyadh 11442,

More information

Renewable Energy. Solar Power. Courseware Sample 86352-F0

Renewable Energy. Solar Power. Courseware Sample 86352-F0 Renewable Energy Solar Power Courseware Sample 86352-F0 A RENEWABLE ENERGY SOLAR POWER Courseware Sample by the staff of Lab-Volt Ltd. Copyright 2009 Lab-Volt Ltd. All rights reserved. No part of this

More information

Development of an Integrated Data Product for Hawaii Climate

Development of an Integrated Data Product for Hawaii Climate Development of an Integrated Data Product for Hawaii Climate Jan Hafner, Shang-Ping Xie (PI)(IPRC/SOEST U. of Hawaii) Yi-Leng Chen (Co-I) (Meteorology Dept. Univ. of Hawaii) contribution Georgette Holmes

More information

TOPIC: CLOUD CLASSIFICATION

TOPIC: CLOUD CLASSIFICATION INDIAN INSTITUTE OF TECHNOLOGY, DELHI DEPARTMENT OF ATMOSPHERIC SCIENCE ASL720: Satellite Meteorology and Remote Sensing TERM PAPER TOPIC: CLOUD CLASSIFICATION Group Members: Anil Kumar (2010ME10649) Mayank

More information

Clouds and the Energy Cycle

Clouds and the Energy Cycle August 1999 NF-207 The Earth Science Enterprise Series These articles discuss Earth's many dynamic processes and their interactions Clouds and the Energy Cycle he study of clouds, where they occur, and

More information

Active Fire Monitoring: Product Guide

Active Fire Monitoring: Product Guide Active Fire Monitoring: Product Guide Doc.No. Issue : : EUM/TSS/MAN/15/801989 v1c EUMETSAT Eumetsat-Allee 1, D-64295 Darmstadt, Germany Tel: +49 6151 807-7 Fax: +49 6151 807 555 Date : 14 April 2015 http://www.eumetsat.int

More information

Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer

Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer I. Genkova and C. N. Long Pacific Northwest National Laboratory Richland, Washington T. Besnard ATMOS SARL Le Mans, France

More information

An Introduction to the MTG-IRS Mission

An Introduction to the MTG-IRS Mission An Introduction to the MTG-IRS Mission Stefano Gigli, EUMETSAT IRS-NWC Workshop, Eumetsat HQ, 25-0713 Summary 1. Products and Performance 2. Design Overview 3. L1 Data Organisation 2 Part 1 1. Products

More information

Forest Fire Information System (EFFIS): Rapid Damage Assessment

Forest Fire Information System (EFFIS): Rapid Damage Assessment Forest Fire Information System (EFFIS): Fire Danger D Rating Rapid Damage Assessment G. Amatulli, A. Camia, P. Barbosa, J. San-Miguel-Ayanz OUTLINE 1. Introduction: what is the JRC 2. What is EFFIS 3.

More information

VALIDATION OF SAFNWC / MSG CLOUD PRODUCTS WITH ONE YEAR OF SEVIRI DATA

VALIDATION OF SAFNWC / MSG CLOUD PRODUCTS WITH ONE YEAR OF SEVIRI DATA VALIDATION OF SAFNWC / MSG CLOUD PRODUCTS WITH ONE YEAR OF SEVIRI DATA M.Derrien 1, H.Le Gléau 1, Jean-François Daloze 2, Martial Haeffelin 2 1 Météo-France / DP / Centre de Météorologie Spatiale. BP 50747.

More information

COMPARISON OF FIXED & VARIABLE RATES (25 YEARS) CHARTERED BANK ADMINISTERED INTEREST RATES - PRIME BUSINESS*

COMPARISON OF FIXED & VARIABLE RATES (25 YEARS) CHARTERED BANK ADMINISTERED INTEREST RATES - PRIME BUSINESS* COMPARISON OF FIXED & VARIABLE RATES (25 YEARS) 2 Fixed Rates Variable Rates FIXED RATES OF THE PAST 25 YEARS AVERAGE RESIDENTIAL MORTGAGE LENDING RATE - 5 YEAR* (Per cent) Year Jan Feb Mar Apr May Jun

More information

COMPARISON OF FIXED & VARIABLE RATES (25 YEARS) CHARTERED BANK ADMINISTERED INTEREST RATES - PRIME BUSINESS*

COMPARISON OF FIXED & VARIABLE RATES (25 YEARS) CHARTERED BANK ADMINISTERED INTEREST RATES - PRIME BUSINESS* COMPARISON OF FIXED & VARIABLE RATES (25 YEARS) 2 Fixed Rates Variable Rates FIXED RATES OF THE PAST 25 YEARS AVERAGE RESIDENTIAL MORTGAGE LENDING RATE - 5 YEAR* (Per cent) Year Jan Feb Mar Apr May Jun

More information

Volcanic Ash Monitoring: Product Guide

Volcanic Ash Monitoring: Product Guide Doc.No. Issue : : EUM/TSS/MAN/15/802120 v1a EUMETSAT Eumetsat-Allee 1, D-64295 Darmstadt, Germany Tel: +49 6151 807-7 Fax: +49 6151 807 555 Date : 2 June 2015 http://www.eumetsat.int WBS/DBS : EUMETSAT

More information

The APOLLO cloud product statistics Web service The APOLLO cloud product statistics Web service

The APOLLO cloud product statistics Web service The APOLLO cloud product statistics Web service The APOLLO cloud product statistics Web service Introduction DLR and Transvalor are preparing a new Web service to disseminate the statistics of the APOLLO cloud physical parameters as a further help in

More information

Towards assimilating IASI satellite observations over cold surfaces - the cloud detection aspect

Towards assimilating IASI satellite observations over cold surfaces - the cloud detection aspect Towards assimilating IASI satellite observations over cold surfaces - the cloud detection aspect Tuuli Perttula, FMI + Thanks to: Nadia Fourrié, Lydie Lavanant, Florence Rabier and Vincent Guidard, Météo

More information

Use of numerical weather forecast predictions in soil moisture modelling

Use of numerical weather forecast predictions in soil moisture modelling Use of numerical weather forecast predictions in soil moisture modelling Ari Venäläinen Finnish Meteorological Institute Meteorological research ari.venalainen@fmi.fi OBJECTIVE The weather forecast models

More information

Estimating Firn Emissivity, from 1994 to1998, at the Ski Hi Automatic Weather Station on the West Antarctic Ice Sheet Using Passive Microwave Data

Estimating Firn Emissivity, from 1994 to1998, at the Ski Hi Automatic Weather Station on the West Antarctic Ice Sheet Using Passive Microwave Data Estimating Firn Emissivity, from 1994 to1998, at the Ski Hi Automatic Weather Station on the West Antarctic Ice Sheet Using Passive Microwave Data Mentor: Dr. Malcolm LeCompte Elizabeth City State University

More information

Validating MOPITT Cloud Detection Techniques with MAS Images

Validating MOPITT Cloud Detection Techniques with MAS Images Validating MOPITT Cloud Detection Techniques with MAS Images Daniel Ziskin, Juying Warner, Paul Bailey, John Gille National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307 ABSTRACT The

More information

ESCI 107/109 The Atmosphere Lesson 2 Solar and Terrestrial Radiation

ESCI 107/109 The Atmosphere Lesson 2 Solar and Terrestrial Radiation ESCI 107/109 The Atmosphere Lesson 2 Solar and Terrestrial Radiation Reading: Meteorology Today, Chapters 2 and 3 EARTH-SUN GEOMETRY The Earth has an elliptical orbit around the sun The average Earth-Sun

More information

Satellite remote sensing using AVHRR, ATSR, MODIS, METEOSAT, MSG

Satellite remote sensing using AVHRR, ATSR, MODIS, METEOSAT, MSG Satellite remote sensing using AVHRR, ATSR, MODIS, METEOSAT, MSG Ralf Meerkötter, Luca Bugliaro, Knut Dammann, Gerhard Gesell, Christine König, Waldemar Krebs, Hermann Mannstein, Bernhard Mayer, presented

More information

Remote Sensing of Contrails and Aircraft Altered Cirrus Clouds

Remote Sensing of Contrails and Aircraft Altered Cirrus Clouds Remote Sensing of Contrails and Aircraft Altered Cirrus Clouds R. Palikonda 1, P. Minnis 2, L. Nguyen 1, D. P. Garber 1, W. L. Smith, r. 1, D. F. Young 2 1 Analytical Services and Materials, Inc. Hampton,

More information

2.3 Spatial Resolution, Pixel Size, and Scale

2.3 Spatial Resolution, Pixel Size, and Scale Section 2.3 Spatial Resolution, Pixel Size, and Scale Page 39 2.3 Spatial Resolution, Pixel Size, and Scale For some remote sensing instruments, the distance between the target being imaged and the platform,

More information

EUMETSAT Satellite Programmes

EUMETSAT Satellite Programmes EUMETSAT Satellite Programmes Nowcasting Applications Developing Countries Marianne König marianne.koenig@eumetsat.int WSN-12 Rio de Janeiro 06-10 August 2012 27 Member States & 4 Cooperating States Member

More information

Precipitation Remote Sensing

Precipitation Remote Sensing Precipitation Remote Sensing Huade Guan Prepared for Remote Sensing class Earth & Environmental Science University of Texas at San Antonio November 14, 2005 Outline Background Remote sensing technique

More information

Retrieval of cloud spherical albedo from top-of-atmosphere reflectance measurements performed at a single observation angle

Retrieval of cloud spherical albedo from top-of-atmosphere reflectance measurements performed at a single observation angle Atmos. Chem. Phys., 7, 3633 3637, 2007 Author(s) 2007. This work is licensed under a Creative Commons License. Atmospheric Chemistry and Physics Retrieval of cloud from top-of-atmosphere reflectance measurements

More information

Astro 301/ Fall 2005 (48310) Introduction to Astronomy

Astro 301/ Fall 2005 (48310) Introduction to Astronomy Astro 301/ Fall 2005 (48310) Introduction to Astronomy Instructor: Professor Shardha Jogee TAs: David Fisher, Donghui Jeong, and Miranda Nordhaus Lecture 22 = Tu Nov 15 Lecture 23 = Th Nov 17 http://www.as.utexas.edu/~sj/a301-fa05/

More information

SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations

SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations SAFNWC/MSG Cloud type/height. Application for fog/low cloud situations 22 September 2011 Hervé LE GLEAU, Marcel DERRIEN Centre de météorologie Spatiale. Lannion Météo-France 1 Fog or low level clouds?

More information

Solar Flux and Flux Density. Lecture 3: Global Energy Cycle. Solar Energy Incident On the Earth. Solar Flux Density Reaching Earth

Solar Flux and Flux Density. Lecture 3: Global Energy Cycle. Solar Energy Incident On the Earth. Solar Flux Density Reaching Earth Lecture 3: Global Energy Cycle Solar Flux and Flux Density Planetary energy balance Greenhouse Effect Vertical energy balance Latitudinal energy balance Seasonal and diurnal cycles Solar Luminosity (L)

More information

GOES-R AWG Cloud Team: ABI Cloud Height

GOES-R AWG Cloud Team: ABI Cloud Height GOES-R AWG Cloud Team: ABI Cloud Height June 8, 2010 Presented By: Andrew Heidinger 1 1 NOAA/NESDIS/STAR 1 Outline Executive Summary Algorithm Description ADEB and IV&V Response Summary Requirements Specification

More information

Comparison of NOAA's Operational AVHRR Derived Cloud Amount to other Satellite Derived Cloud Climatologies.

Comparison of NOAA's Operational AVHRR Derived Cloud Amount to other Satellite Derived Cloud Climatologies. Comparison of NOAA's Operational AVHRR Derived Cloud Amount to other Satellite Derived Cloud Climatologies. Sarah M. Thomas University of Wisconsin, Cooperative Institute for Meteorological Satellite Studies

More information

Towards Operational Monitoring of the Baltic Sea by Remote Sensing

Towards Operational Monitoring of the Baltic Sea by Remote Sensing G. Schernewski & N. Löser (eds.): Managing the Baltic Sea. Coastline Reports 2 (2004), ISSN 0928-2734 S. 211-218 Towards Operational Monitoring of the Baltic Sea by Remote Sensing Andreas Neumann 1, Harald

More information

The APOLLO cloud product statistics Web service

The APOLLO cloud product statistics Web service The APOLLO cloud product statistics Web service Introduction DLR and Transvalor are preparing a new Web service to disseminate the statistics of the APOLLO cloud physical parameters as a further help in

More information

Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius

Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius Evaluation of the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius F.-L. Chang and Z. Li Earth System Science Interdisciplinary Center University

More information

A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS

A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115,, doi:10.1029/2009jd013422, 2010 A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS Roger Marchand, 1 Thomas Ackerman, 1 Mike

More information

USING THE GOES 3.9 µm SHORTWAVE INFRARED CHANNEL TO TRACK LOW-LEVEL CLOUD-DRIFT WINDS ABSTRACT

USING THE GOES 3.9 µm SHORTWAVE INFRARED CHANNEL TO TRACK LOW-LEVEL CLOUD-DRIFT WINDS ABSTRACT USING THE GOES 3.9 µm SHORTWAVE INFRARED CHANNEL TO TRACK LOW-LEVEL CLOUD-DRIFT WINDS Jason P. Dunion 1 and Christopher S. Velden 2 1 NOAA/AOML/Hurricane Research Division, 2 UW/CIMSS ABSTRACT Low-level

More information

Cloud Thickness Estimation from GOES-8 Satellite Data Over the ARM-SGP Site

Cloud Thickness Estimation from GOES-8 Satellite Data Over the ARM-SGP Site Cloud Thickness Estimation from GOES-8 Satellite Data Over the ARM-SGP Site V. Chakrapani, D. R. Doelling, and A. D. Rapp Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis National Aeronautics

More information

How To Forecast Solar Power

How To Forecast Solar Power Forecasting Solar Power with Adaptive Models A Pilot Study Dr. James W. Hall 1. Introduction Expanding the use of renewable energy sources, primarily wind and solar, has become a US national priority.

More information

List 10 different words to describe the weather in the box, below.

List 10 different words to describe the weather in the box, below. Weather and Climate Lesson 1 Web Quest: What is the Weather? List 10 different words to describe the weather in the box, below. How do we measure the weather? Use this web link to help you: http://www.bbc.co.uk/weather/weatherwise/activities/weatherstation/

More information

An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties

An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties Michael Pitts, Chris Hostetler, Lamont Poole, Carl Holden, and Didier Rault NASA Langley Research Center, MS 435,

More information

Spectral Response for DigitalGlobe Earth Imaging Instruments

Spectral Response for DigitalGlobe Earth Imaging Instruments Spectral Response for DigitalGlobe Earth Imaging Instruments IKONOS The IKONOS satellite carries a high resolution panchromatic band covering most of the silicon response and four lower resolution spectral

More information

'Developments and benefits of hydrographic surveying using multispectral imagery in the coastal zone

'Developments and benefits of hydrographic surveying using multispectral imagery in the coastal zone Abstract With the recent launch of enhanced high-resolution commercial satellites, available imagery has improved from four-bands to eight-band multispectral. Simultaneously developments in remote sensing

More information

Case 2:08-cv-02463-ABC-E Document 1-4 Filed 04/15/2008 Page 1 of 138. Exhibit 8

Case 2:08-cv-02463-ABC-E Document 1-4 Filed 04/15/2008 Page 1 of 138. Exhibit 8 Case 2:08-cv-02463-ABC-E Document 1-4 Filed 04/15/2008 Page 1 of 138 Exhibit 8 Case 2:08-cv-02463-ABC-E Document 1-4 Filed 04/15/2008 Page 2 of 138 Domain Name: CELLULARVERISON.COM Updated Date: 12-dec-2007

More information

Cloud Oxygen Pressure Algorithm for POLDER-2

Cloud Oxygen Pressure Algorithm for POLDER-2 Cloud Oxygen ressure Algorithm for OLDER-2 1/7 Cloud Oxygen ressure Algorithm for OLDER-2 Aim of the : Determination of cloud gen pressure from arent pressure by removing the contribution. Date of the

More information

Evaluating GCM clouds using instrument simulators

Evaluating GCM clouds using instrument simulators Evaluating GCM clouds using instrument simulators University of Washington September 24, 2009 Why do we care about evaluation of clouds in GCMs? General Circulation Models (GCMs) project future climate

More information

E-ELT site characterization status

E-ELT site characterization status E-ELT site characterization status Vernin J. a, Muñoz-Tuñon C. b and Sarazin M. c a UMR6525 Fizeau, Nice-Sophia Antipolis University, France; b Instituto de Astrofísica de Canarias (IAC), Tenerife-Spain;

More information

Climatology of aerosol and cloud properties at the ARM sites:

Climatology of aerosol and cloud properties at the ARM sites: Climatology of aerosol and cloud properties at the ARM sites: MFRSR combined with other measurements Qilong Min ASRC, SUNY at Albany MFRSR: Spectral irradiances at 6 six wavelength passbands: 415, 500,

More information

Ionospheric Research with the LOFAR Telescope

Ionospheric Research with the LOFAR Telescope Ionospheric Research with the LOFAR Telescope Leszek P. Błaszkiewicz Faculty of Mathematics and Computer Science, UWM Olsztyn LOFAR - The LOw Frequency ARray The LOFAR interferometer consist of a large

More information

Temporal variation in snow cover over sea ice in Antarctica using AMSR-E data product

Temporal variation in snow cover over sea ice in Antarctica using AMSR-E data product Temporal variation in snow cover over sea ice in Antarctica using AMSR-E data product Michael J. Lewis Ph.D. Student, Department of Earth and Environmental Science University of Texas at San Antonio ABSTRACT

More information

CARBON THROUGH THE SEASONS

CARBON THROUGH THE SEASONS DESCRIPTION In this lesson plan, students learn about the carbon cycle and understand how concentrations of carbon dioxide (CO 2 ) in the Earth s atmosphere vary as the seasons change. Students also learn

More information

For further information, and additional background on the American Meteorological Society s Education Program, please contact:

For further information, and additional background on the American Meteorological Society s Education Program, please contact: Project ATMOSPHERE This guide is one of a series produced by Project ATMOSPHERE, an initiative of the American Meteorological Society. Project ATMOSPHERE has created and trained a network of resource agents

More information

High Resolution Information from Seven Years of ASTER Data

High Resolution Information from Seven Years of ASTER Data High Resolution Information from Seven Years of ASTER Data Anna Colvin Michigan Technological University Department of Geological and Mining Engineering and Sciences Outline Part I ASTER mission Terra

More information

How To Understand Cloud Properties From Satellite Imagery

How To Understand Cloud Properties From Satellite Imagery P1.70 NIGHTTIME RETRIEVAL OF CLOUD MICROPHYSICAL PROPERTIES FOR GOES-R Patrick W. Heck * Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison Madison, Wisconsin P.

More information

Sky Monitoring Techniques using Thermal Infrared Sensors. sabino piazzolla Optical Communications Group JPL

Sky Monitoring Techniques using Thermal Infrared Sensors. sabino piazzolla Optical Communications Group JPL Sky Monitoring Techniques using Thermal Infrared Sensors sabino piazzolla Optical Communications Group JPL Atmospheric Monitoring The atmospheric channel has a great impact on the channel capacity at optical

More information

P1.21 GOES CLOUD DETECTION AT THE GLOBAL HYDROLOGY AND CLIMATE CENTER

P1.21 GOES CLOUD DETECTION AT THE GLOBAL HYDROLOGY AND CLIMATE CENTER P1.21 GOES CLOUD DETECTION AT THE GLOBAL HYDROLOGY AND CLIMATE CENTER Gary J. Jedlovec* NASA/MSFC/Global Hydrology and Climate Center National Space Science and Technology Center Huntsville, Alabama and

More information

TOP-DOWN ISOPRENE EMISSION INVENTORY FOR NORTH AMERICA CONSTRUCTED FROM SATELLITE MEASUREMENTS OF FORMALDEHYDE COLUMNS

TOP-DOWN ISOPRENE EMISSION INVENTORY FOR NORTH AMERICA CONSTRUCTED FROM SATELLITE MEASUREMENTS OF FORMALDEHYDE COLUMNS TOP-DOWN ISOPRENE EMISSION INVENTORY FOR NORTH AMERICA CONSTRUCTED FROM SATELLITE MEASUREMENTS OF FORMALDEHYDE COLUMNS Daniel J. Jacob, Paul I. Palmer, Dorian S. Abbot Atmospheric Chemistry Modeling Group,

More information

Daily High-resolution Blended Analyses for Sea Surface Temperature

Daily High-resolution Blended Analyses for Sea Surface Temperature Daily High-resolution Blended Analyses for Sea Surface Temperature by Richard W. Reynolds 1, Thomas M. Smith 2, Chunying Liu 1, Dudley B. Chelton 3, Kenneth S. Casey 4, and Michael G. Schlax 3 1 NOAA National

More information

Monitoring Soil Moisture from Space. Dr. Heather McNairn Science and Technology Branch Agriculture and Agri-Food Canada heather.mcnairn@agr.gc.

Monitoring Soil Moisture from Space. Dr. Heather McNairn Science and Technology Branch Agriculture and Agri-Food Canada heather.mcnairn@agr.gc. Monitoring Soil Moisture from Space Dr. Heather McNairn Science and Technology Branch Agriculture and Agri-Food Canada heather.mcnairn@agr.gc.ca What is Remote Sensing? Scientists turn the raw data collected

More information

VLT(I) instrument operations and maintenance at the Paranal Observatory

VLT(I) instrument operations and maintenance at the Paranal Observatory VLT(I) instrument operations and maintenance at the Paranal Observatory A. Kaufer a, J. L. Alvarez a, E. Bendek a, F. Caruso a, R. Castillo a, J. Jimenez a, G. Gillet a, N. Haddad a, A. Leiva a, M. Marchesi

More information

Analysis One Code Desc. Transaction Amount. Fiscal Period

Analysis One Code Desc. Transaction Amount. Fiscal Period Analysis One Code Desc Transaction Amount Fiscal Period 57.63 Oct-12 12.13 Oct-12-38.90 Oct-12-773.00 Oct-12-800.00 Oct-12-187.00 Oct-12-82.00 Oct-12-82.00 Oct-12-110.00 Oct-12-1115.25 Oct-12-71.00 Oct-12-41.00

More information

Synoptic assessment of AMV errors

Synoptic assessment of AMV errors NWP SAF Satellite Application Facility for Numerical Weather Prediction Visiting Scientist mission report Document NWPSAF-MO-VS-038 Version 1.0 4 June 2009 Synoptic assessment of AMV errors Renato Galante

More information

The USGS Landsat Big Data Challenge

The USGS Landsat Big Data Challenge The USGS Landsat Big Data Challenge Brian Sauer Engineering and Development USGS EROS bsauer@usgs.gov U.S. Department of the Interior U.S. Geological Survey USGS EROS and Landsat 2 Data Utility and Exploitation

More information

Evaluation of VIIRS cloud top property climate data records and their potential improvement with CrIS

Evaluation of VIIRS cloud top property climate data records and their potential improvement with CrIS Evaluation of VIIRS cloud top property climate data records and their potential improvement with CrIS Dr. Bryan A. Baum (PI) Space Science and Engineering Center University of Wisconsin-Madison Madison,

More information

APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING. Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO***

APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING. Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO*** APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO*** *National Institute for Agro-Environmental Sciences 3-1-3 Kannondai Tsukuba

More information

A long time ago, people looked

A long time ago, people looked Supercool Space Tools! By Linda Hermans-Killam A long time ago, people looked into the dark night sky and wondered about the stars, meteors, comets and planets they saw. The only tools they had to study

More information

G. Karasinski, T. Stacewicz, S.Chudzynski, W. Skubiszak, S. Malinowski 1, A. Jagodnicka Institute of Experimental Physics, Warsaw University, Poland

G. Karasinski, T. Stacewicz, S.Chudzynski, W. Skubiszak, S. Malinowski 1, A. Jagodnicka Institute of Experimental Physics, Warsaw University, Poland P1.7 INVESTIGATION OF ATMOSPHERIC AEROSOL WITH MULTIWAVELENGTH LIDAR G. Karasinski, T. Stacewicz, S.Chudzynski, W. Skubiszak, S. Malinowski 1, A. Jagodnicka Institute of Experimental Physics, Warsaw University,

More information

INVESTIGA I+D+i 2013/2014

INVESTIGA I+D+i 2013/2014 INVESTIGA I+D+i 2013/2014 SPECIFIC GUIDELINES ON AEROSPACE OBSERVATION OF EARTH Text by D. Eduardo de Miguel October, 2013 Introducction Earth observation is the use of remote sensing techniques to better

More information

T.A. Tarasova, and C.A.Nobre

T.A. Tarasova, and C.A.Nobre SEASONAL VARIATIONS OF SURFACE SOLAR IRRADIANCES UNDER CLEAR-SKIES AND CLOUD COVER OBTAINED FROM LONG-TERM SOLAR RADIATION MEASUREMENTS IN THE RONDONIA REGION OF BRAZIL T.A. Tarasova, and C.A.Nobre Centro

More information

Enhanced Vessel Traffic Management System Booking Slots Available and Vessels Booked per Day From 12-JAN-2016 To 30-JUN-2017

Enhanced Vessel Traffic Management System Booking Slots Available and Vessels Booked per Day From 12-JAN-2016 To 30-JUN-2017 From -JAN- To -JUN- -JAN- VIRP Page Period Period Period -JAN- 8 -JAN- 8 9 -JAN- 8 8 -JAN- -JAN- -JAN- 8-JAN- 9-JAN- -JAN- -JAN- -JAN- -JAN- -JAN- -JAN- -JAN- -JAN- 8-JAN- 9-JAN- -JAN- -JAN- -FEB- : days

More information

APPLICATION OF GOOGLE EARTH FOR THE DEVELOPMENT OF BASE MAP IN THE CASE OF GISH ABBAY SEKELA, AMHARA STATE, ETHIOPIA

APPLICATION OF GOOGLE EARTH FOR THE DEVELOPMENT OF BASE MAP IN THE CASE OF GISH ABBAY SEKELA, AMHARA STATE, ETHIOPIA APPLICATION OF GOOGLE EARTH FOR THE DEVELOPMENT OF BASE MAP IN THE CASE OF GISH ABBAY SEKELA, AMHARA STATE, ETHIOPIA Abineh Tilahun Department of Geography and environmental studies, Adigrat University,

More information

Review for Introduction to Remote Sensing: Science Concepts and Technology

Review for Introduction to Remote Sensing: Science Concepts and Technology Review for Introduction to Remote Sensing: Science Concepts and Technology Ann Johnson Associate Director ann@baremt.com Funded by National Science Foundation Advanced Technological Education program [DUE

More information

The Moon. Nicola Loaring, SAAO

The Moon. Nicola Loaring, SAAO The Moon Nicola Loaring, SAAO Vital Statistics Mean distance from Earth Orbital Period Rotational Period Diameter 384,400 km 27.322 days 27.322 days 3476 km (0.272 x Earth) Mass 7.3477 10 22 kg (0.0123

More information

Global Seasonal Phase Lag between Solar Heating and Surface Temperature

Global Seasonal Phase Lag between Solar Heating and Surface Temperature Global Seasonal Phase Lag between Solar Heating and Surface Temperature Summer REU Program Professor Tom Witten By Abstract There is a seasonal phase lag between solar heating from the sun and the surface

More information

Total radiative heating/cooling rates.

Total radiative heating/cooling rates. Lecture. Total radiative heating/cooling rates. Objectives:. Solar heating rates.. Total radiative heating/cooling rates in a cloudy atmosphere.. Total radiative heating/cooling rates in different aerosol-laden

More information

TEST WINNER REPRINT. Solar modules 2010. Which manufacturer? Thin-film o r crystalline silicon? What price? Are there any test results?

TEST WINNER REPRINT. Solar modules 2010. Which manufacturer? Thin-film o r crystalline silicon? What price? Are there any test results? February 2010 2/2010 www.photon.de THE SOLAR POWER MAGAZINE Solar modules 2010 Making the right decision Thin-film o r crystalline silicon? TEST WINNER REPRINT Which manufacturer? What price? China-modules,

More information

The Next Generation Flux Analysis: Adding Clear-Sky LW and LW Cloud Effects, Cloud Optical Depths, and Improved Sky Cover Estimates

The Next Generation Flux Analysis: Adding Clear-Sky LW and LW Cloud Effects, Cloud Optical Depths, and Improved Sky Cover Estimates The Next Generation Flux Analysis: Adding Clear-Sky LW and LW Cloud Effects, Cloud Optical Depths, and Improved Sky Cover Estimates C. N. Long Pacific Northwest National Laboratory Richland, Washington

More information

Near Real Time Blended Surface Winds

Near Real Time Blended Surface Winds Near Real Time Blended Surface Winds I. Summary To enhance the spatial and temporal resolutions of surface wind, the remotely sensed retrievals are blended to the operational ECMWF wind analyses over the

More information

Item 4.1: Atmospheric Observation Panel for Climate Recent climatic events, observing-system changes and report from 17 th Session of AOPC

Item 4.1: Atmospheric Observation Panel for Climate Recent climatic events, observing-system changes and report from 17 th Session of AOPC SC-XX, 4-7 September 2012 Item 4.1: Atmospheric Observation Panel for Climate Recent climatic events, observing-system changes and report from 17 th Session of AOPC Adrian Simmons European Centre for Medium-Range

More information